Category: Games

“Centaur chess” is now run by computers

Remember when man and machine played together to beat the solo computers?  It was not usually about adding the man’s chess judgment to that of the machine, rather the man would decide which computer program to use in a given position, when the programs offered conflicting advice. that was called Centaur Chess, or sometimes “Freestyle chess,” before that term was applied to Fischer Random chess.  For years now, the engines have been so strong that strategy no longer made sense.

But with engine strength came chess engine diversity, as for instance Stockfish and Alpha Zero operate on quite different principles.  So now “which program to use” is once again a live issue.  But the entity making those choices is now a program, not a human being:

A traditional AI chess program, trained to win, may not make sense of a Penrose puzzle, but Zahavy suspected that a program made up of many diverse systems, working together as a group, could make headway. So he and his colleagues developed a way to weave together multiple (up to 10) decisionmaking AI systems, each optimized and trained for different strategies, starting with AlphaZero, DeepMind’s powerful chess program. The new system, they reported in August, played better than AlphaZero alone, and it showed more skill—and more creativity—in dealing with Penrose’s puzzles. These abilities came, in a sense, from self-collaboration: If one approach hit a wall, the program simply turned to another.

Here is the full Steven Ornes piece from Wired.

Why I don’t like Fischer Random 960

As you may know, a major tournament is going on right now, based on a variant of Fischer Random rules, sometimes misleadingly called “Freestyle.”  Subject to some constraints, the pieces are placed into the starting position randomly, so in Fischer Random chess opening preparation is useless.  You have to start thinking from move one.  This is a big advantage in a game where often the entire contest is absorbed into 20-30 moves of advance opening preparation, with little or no real sporting element appearing over the board.

Yet I don’t like Fischer Random, for a few hard to fix reasons:

1. Most of the time, at least prior to the endgame, I don’t understand what is going on.  Even with computer assistance.  I could put in five to ten minutes to study the position, and get a sense of the constraints, but as a spectator I don’t want to do that.  As a relatively high opportunity cost person, I am not going to do that.

1b. Classical chess sometimes generates positions where one does not really understand what is going on.  Then it is thrilling, precisely because it is occasional.  A perpetual “fog of war,” as we receive in Fischer Random, just isn’t that thrilling.  In the opening, for instance, I don’t even know if one player is attempting “a risky strategy.”  I am not sure the player knows either.  And I don’t feel that watching more Fischer Random would change that, as there are hundreds of different possible opening positions, mostly with different properties.

2. The younger players have a notable advantage, because they are better at calculating concrete variations and rely less on intuition.  (We already see this in the current results.)  Experience is simply worth much less in this very novel format.  For any one tournament, that is an interesting intrigue.  But over time it is a bore, as if only rookies and sophomores could win NBA titles.  In fact what spectators enjoy watching is Steph Curry going up against Lebron James, or the analogs in chess.  We want to see Magnus meet Fabiano again, not watch two eighteen-year-olds slug it out.  Sorry, Pragga!  You’ll have your day in the sun.

3. Fischer Random cuts off chess from the rest of its history.   That is otherwise a big advantage of chess over many other games and contests.  I like seeing that a player’s move is connected to say an idea from Tal in the early 1960s, or whatever.  I like “Oh, the Giuoco Piano is making a comeback at top levels,” or “today’s players are more willing to sacrifice the exchange than in the 1970s,” and so on.

4. I get frustrated seeing all those Kings sitting on F1, not able to castle in the traditional sense.  There are rules for castling in Fischer Random, but it feels more like pressing the “hyperspace” button in the old Space Invaders video game than anything else.  Who wants to see a Knight on C1 for twenty-five moves?  Not I.

5. I agree that current opening prep is insanely out of control.  I am fine with the remedy of 25-minutes per player Rapid games, or anything in that range, with increment of course.  Those contests are consistently exciting and they are not forced draws (you can play something weird against the Petroff, or to begin with) nor are they dominated by prep.

6. If you don’t want to watch Rapid, I would rather randomize the first few opening moves than the placement of the pieces.  If you don’t control the first three (seven? ten?) first moves, once again opening prep becomes much tougher.  So what if some games start with 1. b4 b6?  The resulting position is still playable for both sides and furthermore it still makes intuitive sense to chess spectators.  Of course the computers would restrict this randomization to sequences that still are playable for both sides.  The very exact nature of current chess opening prep in fact implies you need only a very small change in the rules to disrupt it, not the kind of huge change represented by Fischer Random.

That all said, I am all for experimentation, it’s just that some of them should be strangled in the crib.

Grandmaster-Level Chess Without Search

Scaling seems to be working here:

The recent breakthrough successes in machine learning are mainly attributed to scale: namely large-scale attention-based architectures and datasets of unprecedented scale. This paper investigates the impact of training at scale for chess. Unlike traditional chess engines that rely on complex heuristics, explicit search, or a combination of both, we train a 270M parameter transformer model with supervised learning on a dataset of 10 million chess games. We annotate each board in the dataset with action-values provided by the powerful Stockfish 16 engine, leading to roughly 15 billion data points. Our largest model reaches a Lichess blitz Elo of 2895 against humans, and successfully solves a series of challenging chess puzzles, without any domain-specific tweaks or explicit search algorithms. We also show that our model outperforms AlphaZero’s policy and value networks (without MCTS) and GPT-3.5-turbo-instruct. A systematic investigation of model and dataset size shows that strong chess performance only arises at sufficient scale. To validate our results, we perform an extensive series of ablations of design choices and hyperparameters.

Here is the full paper by Anian Ruoss, et.al. I guess AI is likely to get better at other things too  — I’ve become numb to the miracles, frankly.

Jimmy Carter is underrated, Thomas Schelling edition

“In the US protocol you have to rehearse the entire process every four months….The French, they never rehearse. And their logic is that if you start rehearsing with the president, people are going to start to know how he thinks and they’re going to be able to influence him.”

But, “When do you think Biden rehearses?” Cerf asks. This is another game he plays with students. “The answer is zero times — he never does it. He always says, ‘I’m going to send someone else instead. Not a good time for me…’ What about Trump? How often do you think Trump did it? And the answer is zero. We said, ‘OK, so let’s not [be] partisan. How often Obama?’ ” He didn’t either, according to Cerf. Presidents, Republican and Democrat, are always far too busy. “The last person to have done it is Carter in the Seventies,”

…The keyholes for this are set 18ft apart on either side of the room, he says. “They have to turn the keys at the same time…The whole arrangement requires two people, so that one serviceman having a bad day cannot decide to blow up the world. “The one thing that they all do at some point is they spend time figuring out how they would do it alone if they needed to,” Cerf says. “They’re not supposed to… [But] they said, ‘Every person in this shift at some point figured out that if they connect the broom to the teapot and hold it like this, they can actually turn the two keys together.’ So they all said, at some point, that they play this mental game of, ‘OK, I can actually start a nuclear war.’ ”

Here is the full Times of London article, gated but very interesting throughout.  Via Jason Dunne.

The death of deterrence?

https://twitter.com/RLHeinrichs/status/1715171574167261313

Not to mention Hamas attacking in the first place (you also can debate at whom the Houthis were aiming, probably not the U.S. per se).  And the 32 dead and 11 Americans unaccounted for.

Forget about moralizing and sides-taking for a moment, and just try to think this through as a game.  Either a) attacks of this nature recur and escalate, or b) the U.S. and/or Israel act to reestablish deterrence?  If b), what kind of act would suffice to reestablish some kind of effective deterrence?  Again, to think clearly please try to steer your attention away from the moral question of what you think the U.S. and/or Israel should do.

I date the decline (but not death) of deterrence to when Iraq fired 42 Scud missiles into Israel in 1991 and the Israelis did not retaliate.  That decision was widely praised at the time, and perhaps correctly.  Still, since then people have been solving for the equilibrium…and now that new equilibrium seems to be upon us.  What would Thomas Schelling say?  This is all worth a very serious ponder.

The Bat the Ball and the Hopeless

You will no doubt be familiar with the bat and ball problem;

  • A bat and a ball cost $1.10 in total.
  • The bat costs $1.00 more than the ball.
  • How much does the ball cost? ____ cents.

In a paper in Cognition, Meyer and Fredrick test multiple versions of the bat and ball and related problems to try to uncover where people’s intuitions go wrong. The most remarkable two versions of which are shown below:

  • A bat and a ball cost $110 in total.
  • The bat costs $100 more than the ball.
  • How much does the ball cost?
  • Before responding, consider whether the answer could be $5.
  •  $_____

———–

  • A bat and a ball cost $110 in total.
  • The bat costs $100 more than the ball.
  • How much does the ball cost?
  • The answer is $5.
  • Please enter the number 5 in the blank below.
  •  $_____

Remarkably, even when told to consider $5, most people continue to answer $10. Even more shockingly, most people get the answer right when they are explicitly told the answer and instructed to enter it, yet 23% still get the answer wrong! Wow.

The authors conclude:

…this “hinted” procedure serves to partition respondents into three groups: the reflective (who reject the common intuitive error and solve the problem on the first try), the careless (who answer 10, but revise to 5 when told they are wrong), and the hopeless (who are unable or unwilling to compute the correct response, even after being told that 10 is incorrect)

…many respondents maintain the erroneous response in the face of facts that plainly falsify it, even after their attention has been directed to those facts….the remarkable durability of that error paints a more pessimistic picture of human reasoning than we were initially inclined to accept; those whose thoughts most require additional deliberation benefit little from whatever additional deliberation can be induced.

As an economist, I would have liked to see an incentivized version (maybe some people are pulling the authors legs) but I don’t actually think that explains the results. Quite a few people are indeed hopeless.

My Conversation with Vishy Anand

In Chennai I recorded with chess great Vishy Anand, here is the transcript, audio, and video, note the chess analysis works best on YouTube, for those of you who follow such things (you don’t have to for most of the dialogue).  Here is the episode summary:

Tyler and Vishy sat down in Chennai to discuss his breakthrough 1991 tournament win in Reggio Emilia, his technique for defeating Kasparov in rapid play, how he approached playing the volatile but brilliant Vassily Ivanchuk at his peak, a detailed breakdown of his brilliant 2013 game against Levon Aronian, dealing with distraction during a match, how he got out of a multi-year slump, Monty Python vs. Fawlty Towers, the most underrated Queen song, how far to take chess opening preparation, which style of chess will dominate in the next ten years, how AlphaZero changes what we know about the game, the key to staying a top ten player at age 53, why he thinks he’s a worse loser than Kasparov, qualities he looks for in talented young Indian chess players, picks for the best places to eat in Chennai, and more.

Here is one excerpt:

COWEN: Do you hate losing as much as Kasparov does?

ANAND: To me, it seems he isn’t even close to me, but I admit I can’t see him from the inside, and he probably can’t see me from the inside. When I lose, I can’t imagine anyone in the world who loses as badly as I do inside.

COWEN: You think you’re the worst at losing?

ANAND: At least that I know of. A couple of years ago, whenever people would say, “But how are you such a good loser?” I’d say, “I’m not a good loser. I’m a good actor.” I know how to stay composed in public. I can even pretend for five minutes, but I can only do it for five minutes because I know that once the press conference is over, once I can finish talking to you, I can go back to my room and hit my head against the wall because that’s what I’m longing to do now.

In fact, it’s gotten even worse because as you get on, you think, “I should have known that. I should have known that. I should have known not to do that. What is the point of doing this a thousand times and not learning anything?” You get angry with yourself much more. I hate losing much more, even than before.

COWEN: There’s an interview with Magnus on YouTube, and they ask him to rate your sanity on a scale of 1 to 10 — I don’t know if you’ve seen this — and he gives you a 10. Is he wrong?

ANAND: No, he’s completely right. He’s completely right. Sanity is being able to show the world that you are sane even when you’re insane. Therefore I’m 11.

COWEN: [laughs] Overall, how happy a lot do you think top chess players are? Say, top 20 players?

ANAND: I think they’re very happy.

Most of all, I was struck by how good a psychologist Vishy is.  Highly recommended, and you also can see whether or not I can keep up with Vishy in his chess analysis.  Note I picked a game of his from ten years ago (against Aronian), and didn’t tell him in advance which game it would be.

Ken Rogoff on chess and AI

From an interview:

Rogoff, who is also the Maurits C. Boas Chair of International Economics at Harvard University, doesn’t see artificial intelligence as bad for chess. “It’s actually made it more interesting so far,” he says.

Having seen how fast AI evolved within the game, Rogoff predicts applications like ChatGPT will be unrecognizable in five years. Advancements will come “faster than you think,” but if the experience of chess is any indication, the technology’s evolution won’t be as “detrimental” as some may fear…

I don’t want to sound evangelical, because I don’t know which way it’s going to go. But, yes. If you look at the experience of chess faster than you think and for longer than you think but also not necessarily as detrimental as you might think. Humans have adjusted. And it’s been very good.

JULIE HYMAN: Well, can you elaborate on that a little bit? You said it’s made chess more interesting. How?

KENNETH ROGOFF: Well, first of all, people have thought a lot of positions were boring. That the computer shows, well, try me at this position, and it turns out to be just wellsprings of creativity positions, where the best player in the world, Bobby Fischer, I think would have maybe even given me a draw back in 1975. Now is the beginning of the game for many players, so this depth of learning. Players venture much more complicated and interesting positions because they have other ways to explore them.

So surprisingly, we thought it would lead to more draws, right? If you figured out better, you’re going to get more draws. Not at all. So here’s this simple compared to human intelligence game, which you would think you would solve out, and yet you find these layers of interest. I think we’ll see this in art and many, many things.

Here is the link, it references the longer chat with some economics of debt and inflation.

My excellent Conversation with Reid Hoffman

Here is the audio, video, and transcript.  Here is the episode summary:

In his second appearance, Reid Hoffman joined Tyler to talk everything AI: the optimal liability regime for LLMs, whether there’ll be autonomous money-making bots, which agency should regulate AI, how AI will affect the media ecosystem and the communication of ideas, what percentage of the American population will eschew it, how gaming will evolve, whether AI’s future will be open-source or proprietary, the binding constraint preventing the next big step in AI, which philosopher has risen in importance thanks to AI, what he’d ask a dolphin, what LLMs have taught him about friendship, how higher education will change, and more. They also discuss Sam Altman’s overlooked skill, the biggest cultural problem in America, the most underrated tech scene, and what he’ll do next.

Here is one excerpt:

COWEN: Given GPT models, which philosopher has most risen in importance in your eyes? Some people say Wittgenstein. I don’t think it’s obvious.

HOFFMAN: I think I said Wittgenstein earlier. In Fireside Chatbots, I brought in Wittgenstein in language games.

COWEN: Peirce maybe. Who else?

HOFFMAN: Peirce is good. Now I happen to have read Wittgenstein at Oxford, so I can comment in some depth. The question about language and language games and forms of life and how these large language models might mirror human forms of life because they’re trained on human language is a super interesting question, like Wittgenstein.

Other good language philosophers, I think, are interesting. That doesn’t necessarily mean philosophy-of-language philosophers à la analytic philosophy. Gareth Evans, theories of reference as applied to how you’re thinking about this kind of stuff, is super interesting. Christopher Peacocke’s concept work is, I think, interesting.

Anyway, there’s a whole range of stuff. Then also the philosophy, all the neuroscience stuff applied with the large language models, I think, is very interesting as well.

COWEN: What in science fiction do you feel has risen the most in status for you?

HOFFMAN: Oh, for me.

COWEN: Not in the world. We don’t know yet.

HOFFMAN: Yes. We don’t know yet.

COWEN: You think, “Oh, this was really important.” Vernor Vinge or . . .

HOFFMAN: Well, this is going to seem maybe like a strange answer to you, but I’ve been rereading David Brin’s Uplift series very carefully because the theory of, “How should we create other kinds of intelligences, and what should that theory be, and what should be our shepherding and governance function and symbiosis?” is a question that we have to think about over time. He went straight at this in a biological sense, but it’s the same thing, just a different substrate with the Uplift series. I’ve recently reread the entire Uplift series.

Self-recommending!

What game theory predicts

In most of the equilibria I can conceive, either Prighozin or Putin has to die in the next week or less? Putin has to die if he can’t take out Prighozin promptly?

Game theory is often wrong, but it is worth putting this prediction out there.  And here is Kamil Galeev on the most likely equilibrium, I tend to agree with him:

Game theory and the First World War

By Nobel Laureate Roger Myerson:

Books by Scott Wolford and Roger Ransom show how economic theories of games and decisions can be fruitfully applied to problems in World War I. This vital application offers fundamental insights into the analytical methods of game theory. Public random variables may be essential factors in war-of-attrition games. An assumption that nations can coordinate on Pareto-superior equilibria may become less tenable when nations are at war. Interpreting a surprising mistake as evidence of an unlikely type can have serious consequences. The ability of leaders to foster consistent beliefs within a cohesive society can create inconsistency of beliefs between nations at war.

Just published in the (ungated) Journal of Economic Literature.

The art of prompting is just at its beginning

And here are some results for Minecraft.  I would like to see confirmations, but these are credible sources and this is all quite important if true.